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. 2022 Jan 27;12:1528. doi: 10.1038/s41598-022-05612-1

Dominance of Asia II 1 species of Bemisia tabaci in Pakistan and beyond

Muhammad Arslan Mahmood 1, Nasim Ahmed 1, Sonia Hussain 1, Sidra Tul Muntaha 1, Imran Amin 1, Shahid Mansoor 1,✉
PMCID: PMC8795192  PMID: 35087224

Abstract

Globally, Whitefly (Bemisia tabaci) is one of the most important insect pests of crops that causes huge economical losses. The current study was designed to exclusively screen the B. tabaci species in the cotton field of Pakistan during 2017–2020 and have to conduct comparative analysis of B. tabaci species in Asia where Asia II 1 has been reported. A total of 5142 B. tabaci sequences of mitochondrial cytochrome oxidase 1 (mtCO1) from Asian countries were analyzed to determine the species and their distribution in the region. Our analysis over time and space showed that Asia II 1 has gradually dominated over Asia 1 in Punjab Province and over both Asia 1 and MEAM1 in Sindh Province. Asia has been divided into three regions i.e., South Asia (2524 sequences), Southeast Asia (757 sequences) and East Asia (1569 sequences) and dominance of different species of B. tabaci has been determined by calculating the relative percentage of each species. Interestingly, Asia II 1 has been found dominant in the neighboring region (northern zone) of India and also being dominant in its central zone. The dominance of Asia II 1 in Pakistan and northern India explains whitefly epidemic being reported in recent years.

Subject terms: Biological techniques, Genetics, Molecular biology

Introduction

Cotton (Gossypium spp.) is one of the most important fiber producing and oil-yielding crops. In terms of production, Pakistan is among the top 5 cotton producing countries including China, India, Brazil, and USA1. With the passage of time, its production decreased due to multiple biotic and abiotic factors. Among the biotic factors, insect pests are the major factor that cause losses of up to 2.5 million bales2. Insect pests of cotton can be divided into two major categories; chewing insects and sap-sucking insects. Chewing insects mainly consists of cotton bollworm (Helicoverpa armigera), spotted bollworm (Earias insulana), pink bollworm (Pectinophora gossypiella), and armyworm (Spodoptera littoralis) while sucking insects include whitefly (Bemisia tabaci), aphids (Aphis gossypii), jassids mealybug, and thrips (Thrips tabaci).

There are more than 1000 species of whiteflies3 among them Bemisia tabaci (Gennadius; Hemiptera: Aleyrodidae) is distinguished from others because of its invasiveness and fitness to the environment. It has broad host range with some host preferences. Most of the host plants of B. tabaci belong to the family Cucurbitaceae, Euphorbiaceae, Malvaceae, and Solanaceae such as cotton, tomato, eggplant, cucumber, squash, cassava, and okra, etc4,5. It drains the plants’ nutrients by sucking the phloem sap and also causes indirect damage by secreting honeydew which promotes fungal growth. It can transmit more than 400 plant viruses6 that belong to different virus genera including Begomovirus, Crinivirus, Torradovirus, and Ipomovirus. Its ability to transmit the virus in some economically important crops makes it a more devastating pest. Particularly, the complex of Begomovirus and B. tabaci is proved to be more destructive for crops in developing countries. B. tabaci collectively causes economic loss of billions of dollars around the world every year.

Bemisia tabaci is not a single species but a complex of 46 cryptic species that includes, Africa, Asia I, Asia II 1–12, Asia 1-India, Asia III, Asia IV, Asia V, Australia, Australia/Indonesia, China1-7, Indian Ocean, Ru, Middle East Asia Minor I-II (MEAM), Mediterranean (MED), MEAM K, New World 1–2. Japan 1–2, Uganda, Italy 1, and Sub Saharan Africa 1–57. These species have different and overlapping biological traits. Earlier, these species were referred to as biotypes. The differentiation of these biotypes was based on the biological characteristics which primarily include the capacity to transmit viruses, variation in host range, physiological changes in host plants, capacity to produce female offspring following interspecies mating trails, capacity to disperse widely and insecticide resistance.

Biological traits were not sufficient to separate groups because of plasticity and variability of traits within and between groups. Allozymes markers (primarily esterase) were the first molecular approach to resolve the diversity within the B. tabaci8,9. Based on esterase profiling biotypes were alphabetically designated from A to T. Some other molecular markers, mt16S ribosomal DNA, mitochondrial cytochrome oxidase 1 (mtCO1) and the nuclear ribosomal intergenic spacer 1 (ITS1) were also explored to find the genetic differences among biotypes. The mtCO1 gene is highly valuable and has been widely used for classifying haplotypes of B. tabaci and its close relatives. Based on threshold of 3.5% pairwise genetic divergence in mtCO1, the B. tabaci was resolved into complete or partial reproductively isolated groups. Lee et al.10 suggested that the threshold of the species boundary in the B. tabaci complex is required to be replaced with 4% genetic divergence. Based on mtCO1 sequences a revised nomenclature was established which tells the geographical affiliation of genetic groups. The term biotype was abandoned and genetic groups were described as cryptic species of B. tabaci complex.

The two highly invasive whitefly species, MEAM1 and MED originated from Middle East regions, are now invading other countries of the world11. In Pakistan, MEAM1 is mainly found in the southern region (Sindh province) while Asia II 1 is the most prevalent species in central and north western regions. Other than these species, Asia 1, Asia II 5, Asia II 7, and Asia II 8 have also been reported from Pakistan12.

The current study was designed to explore the genetic diversity of B. tabaci on cotton crop with mtCO1 marker in Pakistan. The second objective was to check the genetic diversity of B. tabaci in other Asian countries including all three major Asia regions including South Asia, South East Asia, and East Asia. Moreover, recently, Asia II 1 is also reported from Syria in Middle East region so the last objective was to check the status of different species of B. tabaci in Middle East countries. The findings of this study have described the current status of different species of B. tabaci in Asian countries. This will be helpful for the development of future management strategies to control this devastating pest in the region.

Results

B. tabaci infestation; a major constraint to cotton production in Pakistan

In the last few years, cotton production in Pakistan is dramatically decreased due to various reasons. The data present in Fig. 1A shows the comparison of cotton production from year 2014 to 2021. There is a marked decrease in the production of cotton. In year 2014, the cotton production was 13.9 million bales which reduced to almost half i.e., 7 million bales in 2020–2021. The data present in Fig. 1B shows 2X infestation in year 2020 in comparison of year 2019, where the infestation percentage was 11.64%.

Figure 1.

Figure 1

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(A) Cotton production of Pakistan (B) Whitefly infestation in cotton belt of Punjab, Pakistan.

Identification of B. tabaci species from Pakistan

Samples of whitefly were collected from 2017 to 2020 from different provinces (Punjab and Sindh) of the country (Fig. 2). Collectively, we identified 80/82 sequences of Asia II 1 and 2/82 sequences of Asia II 7 species from Pakistan. No other species was detected in the current study. Asia II 7 was only detected from samples collected from Islamabad; the city in northern areas that is not the major cotton growing areas. The samples detail which was collected in the current study is summarized in Table 1.

Figure 2.

Figure 2

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Map of Pakistan showing labelled districts, from where samples of B. tabaci were collected. The map was generated using CorelDRAW 12 software and edited in Paint 3D and Microsoft PowerPoint 2019.

Table 1.

Detail of B. tabaci sequences identified in the current study.

Sr. # Acc. # Species Province City Latitude Longitude Isolate Col. Year
1 MZ313270 Asia II 1 Punjab Yazman 29.14467N 71.73595E AW-3 2020
2 MZ313271 Asia II 1 Punjab Yazman 29.146170N 71.743499E AW-4 2020
3 MZ313272 Asia II 1 Punjab Yazman 29.146170N 71.746760E AW-5 2020
4 MZ313273 Asia II 1 Punjab Yazman 29.137623N 71.756717E AW-6 2020
5 MZ313274 Asia II 1 Punjab Yazman 29.132226N 71.734229E AW-7 2020
6 MZ313275 Asia II 1 Punjab Yazman 29.129527N 71.761008E AW-8 2020
7 MZ313276 Asia II 1 Punjab Yazman 29.124428N 71.737662E AW-9 2020
8 MZ313277 Asia II 1 Punjab Yazman 29.108081N 71.738520E AW-10 2020
9 MZ313278 Asia II 1 Punjab Yazman 29.097132N 71.744872E AW-11 2020
10 MZ313279 Asia II 1 Punjab Bahawalpur 29.347898N 71.671470E AW-13 2020
11 MZ313280 Asia II 1 Punjab Bahawalpur 29.358711N 71.652937E AW-14 2020
12 MZ313281 Asia II 1 Punjab Bahawalpur 29.364974N 71.735778E AW-15 2020
13 MZ313282 Asia II 1 Punjab Chistian 29.797352N 72.836743E AW-16 2020
14 MZ313283 Asia II 1 Punjab Chistian 29.795341N 72.835606E AW-17 2020
15 MZ313284 Asia II 1 Punjab Chistian 29.790987N 72.834200E AW-18 2020
16 MZ313285 Asia II 1 Punjab Chistian 29.781153N 72.844457E AW-19 2020
17 MZ313286 Asia II 1 Punjab Bahawalnagar 30.028904N 73.229412E AW-20 2020
18 MZ313287 Asia II 1 Punjab Bahawalnagar 30.014449N 73.230711E AW-21 2020
19 MZ313288 Asia II 1 Punjab Bahawalnagar 30.010527N 73.229655E AW-22 2020
20 MZ313289 Asia II 1 Punjab Rajanpur 29.112637N 70.317262E AW-23 2020
21 MZ313290 Asia II 1 Punjab Rajanpur 29.114078N 70.313188E AW-24 2020
22 MZ313291 Asia II 1 Punjab Rajanpur 29.113994N 70.316668E AW-25 2020
23 MZ313292 Asia II 1 Punjab Rajanpur 29.111647N 70.309053E AW-26 2020
24 MZ313293 Asia II 1 Punjab Rajanpur 29.104118N 70.311337E AW-27 2020
25 MZ313294 Asia II 1 Punjab Haronabad 29.627958N 73.120594E AW-28 2020
26 MZ313295 Asia II 1 Punjab Haronabad 29.634530N 73.137314E AW-29 2020
27 MZ313296 Asia II 1 Punjab Haronabad 29.608393N 73.152638E AW-30 2020
28 MZ313297 Asia II 1 Punjab Haronabad 29.596281N 73.149364E AW-31 2020
29 MZ313298 Asia II 1 Punjab Haronabad 29.594717N 73.147816E AW-32 2020
30 MZ313299 Asia II 1 Punjab Faisalabad 31.397675N 73.026141E AW-33 2020
31 MZ313300 Asia II 1 Punjab Layyah 30.984232N 70.928402E AW-36 2020
32 MZ313301 Asia II 1 Punjab Layyah 30.979178N 70.927938E AW-37 2020
33 MZ313302 Asia II 1 Punjab Sahiwal 30.677757N 73.041449E AW-39 2020
34 MZ313303 Asia II 1 Sindh Tando Allahyar 25.472777N 68.724987E AW-41 2020
35 MZ313304 Asia II 1 Sindh Mirpur Khas 25.506464N 69.003288E AW-42 2020
36 MZ313305 Asia II 7 Punjab Islamabad 33.662970N 73.124633E AW-44 2020
37 MZ313306 Asia II 7 Punjab Islamabad 33.665728N 73.127134E AW-45 2020
38 MZ313307 Asia II 1 Punjab Islamabad 33.671428N 73.125817E AW-46 2020
39 MZ313308 Asia II 1 Punjab Islamabad 33.673854N 73.118686E AW-47 2020
40 MK357328 Asia II 1 Punjab TT Singh 30.977921N 72.466899E STM-1 2017
41 MK357329 Asia II 1 Punjab TT Singh 30.981035N 72.462602E STM-2 2017
42 MK357330 Asia II 1 Punjab TT Singh 30.972902N 72.471313E STM-3 2017
43 MK357331 Asia II 1 Punjab TT Singh 30.955377N 72.474908E STM-4 2017
44 MK357332 Asia II 1 Punjab Vehari 30.062332N 72.340713E STM-5 2017
45 MK357333 Asia II 1 Punjab Vehari 30.062413N 72.332172E STM-6 2017
46 MK357334 Asia II 1 Punjab Vehari 30.060854N 72.329262E STM-7 2017
47 MK357335 Asia II 1 Punjab Vehari 30.059187N 72.325681E STM-8 2017
48 MK357336 Asia II 1 Punjab Multan 30.167339N 71.572929E STM-9 2017
49 MK357337 Asia II 1 Punjab Multan 30.166079N 71.570058E STM-13 2017
50 MK357338 Asia II 1 Punjab Multan 30.259145N 71.541788E STM-14 2017
51 MK357339 Asia II 1 Punjab Multan 30.263070N 71.436380E STM-15 2017
52 MK357340 Asia II 1 Punjab Sahiwal 30.619366N 73.079417E STM-16 2017
53 MK357341 Asia II 1 Punjab Sahiwal 30.630009N 73.069540E STM-17 2017
54 MK357342 Asia II 1 Punjab Sahiwal 30.612582N 73.069595E STM-18 2017
55 MK357343 Asia II 1 Punjab Sahiwal 30.608004N 73.099384E STM-19 2017
56 MK357344 Asia II 1 Punjab D.G. Khan 30.048206N 70.677084E STM-20 2017
57 MK357345 Asia II 1 Punjab D.G. Khan 30.044698N 70.676435E STM-21 2017
58 MK357346 Asia II 1 Punjab D.G. Khan 30.045584N 70.670634E STM-22 2017
59 MK357347 Asia II 1 Punjab D.G. Khan 30.050709N 70.669943E STM-25 2017
60 MK357348 Asia II 1 Punjab TT Singh 30.959737N 72.483569E STM-26 2018
61 MK357349 Asia II 1 Punjab TT Singh 30.958983N 72.483548E STM-28 2018
62 MK357350 Asia II 1 Punjab TT Singh 30.956623N 72.484775E STM-29 2018
63 MK357351 Asia II 1 Punjab TT Singh 30.952657N 72.482393E STM-30 2018
64 MK357352 Asia II 1 Punjab Vehari 30.033080N 72.362021E STM-33 2018
65 MK357353 Asia II 1 Punjab Vehari 30.033674N 72.364478E STM-34 2018
66 MK357354 Asia II 1 Punjab Vehari 30.033785N 72.366474E STM-35 2018
67 MK357355 Asia II 1 Punjab Vehari 30.032717N 72.367000E STM-36 2018
68 MK357356 Asia II 1 Punjab Vehari 30.028398N 72.367730E STM-37 2018
69 MK357357 Asia II 1 Punjab Multan 30.130419N 71.571077E STM-38 2018
70 MK357358 Asia II 1 Punjab Multan 30.129276N 71.574950E STM-39 2018
71 MK357359 Asia II 1 Punjab Multan 30.128144N 71.573845E STM-40 2018
72 MK357360 Asia II 1 Punjab Multan 30.202989N 71.596566E STM-41 2018
73 MK357361 Asia II 1 Punjab Multan 30.270839N 71.592235E STM-42 2018
74 MK357362 Asia II 1 Punjab Sahiwal 30.651294N 73.129210E STM-43 2018
75 MK357363 Asia II 1 Punjab Sahiwal 30.649254N 73.127086E STM-44 2018
76 MK357364 Asia II 1 Punjab Sahiwal 30.649965N 73.123030E STM-45 2018
77 MK357365 Asia II 1 Punjab Sahiwal 30.637863N 73.108079E STM-46 2018
78 MK357366 Asia II 1 Punjab Sahiwal 30.637992N 73.102178E STM-47 2018
79 MK357367 Asia II 1 Punjab D.G. Khan 30.050365N 70.669906E STM-48 2018
80 MK357368 Asia II 1 Punjab D.G. Khan 30.048878N 70.673560E STM-49 2018
81 MK357369 Asia II 1 Punjab D.G. Khan 30.046821N 70.670049E STM-50 2018
82 MK357370 Asia II 1 Punjab D.G. Khan 30.014736N 70.629576E STM-51 2018
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Phylogenetic analysis of mtCO1 sequences of B. tabaci

Phylogenetic dendrogram was constructed using 82 nucleotide mtCO1 sequences of B. tabaci and B. tuberculata as an outgroup. Tree analysis showed the presence of two species of B. tabaci in the current study. No other species of B. tabaci was identified in the current study. The samples (MZ313303, MZ313304) collected from the Sindh cotton growing areas, were also showing the similarity with Asia II 1. The neighbor-joining phylogenetic tree was reconstructed to infer the relationship of the sequences identified in the current study is shown in Fig. 3A and B.

Figure 3.

Figure 3

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(A) A neighbor-joining phylogenetic tree was reconstructed to infer the relationship of mtCO1 sequences identified in the current study with the already known species of B. tabaci. Tree was rooted on the sequence of Bemisia tuberculata (AY057220) species and a total of 113 sequences were used in this analysis including 82 sequences identified in the current study and other reference sequences of some other species. The multiple sequences alignment was carried out by MUSCLE program in MEGA7 software32. Bootstrap method was used with 1000 replications and the percentage bootstrap value (greater than 50%) is shown on each breach. The 80 sequences identified in the current study made the group with Asia II 1 reference sequences (n = 3) and this group is collapsed at the top of the tree showing Asia II 1 (n = 82) whereas two sequences identified in the current study made the clade with Asia II 7 reference sequences. The isolates of the current study are labelled with red circle in the start of their mentioned name in the tree. (B) A neighbor-joining phylogenetic tree was reconstructed by using the current sequences and the reference sequences of only species identified in the current study and an out-group sequence mentioned above. This was included to show the relations among the sequences of the current study that was collapsed in (A).

Distribution of B. tabaci in Pakistan at the province level

In total 1096 sequences were so far reported from Pakistan after removing the 5’ mtCOI gene sequences and also those sequences that contain somehow wrong information (actually they belong to some other species of Bemisia genus). These 1096 sequences were phylogenetically analyzed to determine their species. There were eight species presently named as Asia II 1, MEAM1, Asia II 7, Asia 1, Asia II 5, Asia II 8, Pakistan and Pakistan 1. A single sequence (KJ709461) named as “Pakistan” species was previously reported from Islamabad13 whereas a single sequence (GU585374) was named “Pakistan-1” during the current analysis and according to GenBank submission data it was reported from Sindh province of Pakistan. The relative percentage of each species was determined and shown in the pie diagram against each province in Fig. 4. The Asia II 1 species showed the highest relative % in Balochistan, KPK and Punjab provinces where MEAM1 showed the highest relative % in Sindh province followed by Asia II 1 species.

Figure 4.

Figure 4

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Distribution of B. tabaci in Pakistan at province level. The relative % age of each species is shown in pie diagram against each province. The map was generated using CorelDRAW 12 software and edited in Paint 3D and Microsoft PowerPoint 2019.

To further elaborate the situation, relative % of each species was determined with the timeline (an interval of 5 years). The relative % of different species of B. tabaci reported from 2001 to 2005, 2006–2010, 2011–2015 and 2016–2020, shown in Fig. 5A–D.

Figure 5.

Figure 5

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Relative % age of each species was determined with the timeline (an interval of five years). The relative % age of different species of B. tabaci reported from 2001 to 2005, 2006–2010, 2011–2015 and 2016–2020. The map was generated using CorelDRAW 12 software and edited in Paint 3D and Microsoft PowerPoint 2019.

Distribution of B. tabaci from other countries in South Asia

In total 1166 sequences were so far reported from India after removing the 5′ mtCOI gene sequences and those sequences which contain incomplete information (they were belonging to some other species of Bemisia genus). These 1166 sequences were analyzed to determine their species. The data present in Fig. 6A shows the relative % age of B. tabaci species in India where Asia 1 is dominant over the Asia II 1, Asia II 5, Asia II 7, and Asia II 8. As India is very large country as compared to Pakistan so its zones were used for the comparison of different species in these zones. Overall, India is divided into 6 zones, out of these, B. tabaci is reported from five zones shown in Fig. 6B with the relative % age of each species reported. Like Pakistan, Asia II 1 is dominant in its neighboring zone of India i.e., Northern zone. Interestingly it is also dominant in Central zone of India.

Figure 6.

Figure 6

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Distribution of different species of B. tabaci in other countries of South Asia. (A) The relative % of different species of B. tabaci so far reported from India. (B) The relative % of different species of B. tabaci from different zones of India. (C) The relative % of different species of B. tabaci from Bangladesh and (D) The relative % of different species of B. tabaci from Nepal.

The other countries of South Asia where B. tabaci has been reported are Bangladesh, Nepal and Afghanistan. The relative % of each species from Bangladesh and Nepal is shown in Fig. 6C and (D) respectively. From Afghanistan only two species i.e., Asia 1 and Asia II 5 with few sequences were reported (data not shown here). Moreover, a list of all sequences analyzed is provided in the supplementary file S2, Table S1.

Distribution and genetic variation of B. tabaci in South East Asian countries

Different species of B. tabaci have been reported from eight countries of South East Asia including Indonesia, Myanmar, Singapore, Cambodia, Vietnam, Philippines, Thailand and Malaysia. The largest number of sequences have been reported from Malaysia where Asia 1 species have the largest number of sequences so far reported followed by MED, Asia II 6, China 2, Asia II 7, China 1, and Asia II 10. The relative % these species reported from Malaysia have been shown in Fig. 7A. Interestingly, Asia II 1 is still not reported from Malaysia but it has been reported from some other countries in the Southeast Asian region like Cambodia, Thailand and Vietnam. The overall combined trend of distribution of different species of B. tabaci in these countries is shown in Fig. 7B. Moreover, a list of all sequences analyzed is provided in the supplementary file S2, Table S2.

Figure 7.

Figure 7

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Bemisia tabaci species distribution in South East Asia. (A) The relative % of each species of B. tabaci so far reported from Malaysia, (B) shows the relative % of different species of B. tabaci collectively reported from other countries in South East Asia.

Distribution and genetic variation of B. tabaci in East Asia and Middle East countries

In East Asia, the largest number of sequences of B. tabaci have been reported from China. So, the analysis of data from China is separately described in Fig. 8A. MED is dominant in China followed by MEAM1, Asia 1 and others. The other countries of East Asia region where B. tabaci has been reported are Japan, South Korea and Taiwan. The relative % of different species of B. tabaci collectively from the other countries in East Asia region is shown in Fig. 8B. The relative % of different species of B. tabaci collectively from countries in Middle East is shown in Fig. 8C. The list of sequences of East Asia are provided in supplementary file S2, Table S3 whereas sequences of Middle East are provided in supplementary file S2, Table S4.

Figure 8.

Figure 8

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Bemisia tabaci species distribution in East Asian countries. (A) The relative % of different species of B. tabaci so far reported from China, (B) The relative % of different species of B. tabaci collectively from other countries in East Asian region, (C) The relative % of different species of B. tabaci from Middle East countries.

Prevalence of Asia II 1 species in Asia

Asia II 1 species has been confirmed from 10 countries including Pakistan, India, Bangladesh, Nepal, Cambodia, Vietnam, Thailand, Taiwan, China and Syria. The list of species so far reported from each country has been summarized in supplementary file S1, Table 1. The map of the countries where Asia II 1 species has been reported is shown in Fig. 9.

Figure 9.

Figure 9

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Geographical distribution of B. tabaci species across the world. The presence of different species identified from different geographical locations is indicated in multiple colors. Asia II 1 identified from different countries is in bold font. The world map was collected from https://simplemaps.com and modified using CorelDRAW 12.

Conclusion and future outlook

In the present study, it has been found that B. tabaci species, Asia II 1 is dominant in Pakistan and its spread in comparison with other species has been determined from other Asian countries. This reports the overall situation of different species of B. tabaci in the region. In the future, similar study can be designed to determine the B. tabaci species from the remaining parts of the world. That will be helpful to understand the overall global situation of different B. tabaci species. Secondly, there is a need to explore the tripartite interactions at the molecular level to deeply understand the compatible interaction of specific viruses with vectors and hosts. This deeper understanding will be help break the compatible interaction and will put a way forward to the development of resistant cultivars.

Discussion

In agriculture, species invasion is among the most important factors which drives the changes in natural equilibria and also it has been a major threat to crop production. Insect has the ability to adapt according to the environmental changes and such changes have often been due to genetic changes14. B. tabaci has become the paradigm for both genetic variability and invasiveness in various countries worldwide. The present study is significant because it provides the overall situation about the B. tabaci populations belonging to different species in the Asian countries of the world. The current situation of B. tabaci species in Pakistan is revealed by this study where the dominance of Asia II 1 over the Asia 1, MEAM1 and other species found in Pakistan has been documented. The available sequences (till 1st June 2021) of mtCO1 gene of B. tabaci were analyzed to determine their species in these regions. However, this conclusion has been taken based on the available sequences of mtCO1 gene of B. tabaci that may have bias in collecting and submitting of the sequence. Country-wise data is provided with species and years of reporting that shows the overall situation of B. tabaci genetic variation in these countries.

In Pakistan, we found the dominance of Asia II 1 in major cotton growing regions whereas in its north central region (Islamabad), Asia II 7 was also identified15. One interesting finding in the current analysis is that Asia 1 has disappeared since 2012 from the country. This shows the dominance of Asia II 1 over Asia 1 in Pakistan over the time. In India, Asia 1 is the most dominant species followed by Asia II 1 and others7,16. Recently, in a broader survey in India it has been found that Asia II 1 is dominant in its northern region that shows a situation similar to that of Pakistan. The major reason behind this dominance is probably the excessive use of insecticides and the development of insecticide resistance in Asia II 1 species. Due to the extensive use of insecticide, rapid development of resistance has been reported in Asia II 1 and Asia 1 species of B. tabaci17. Insecticides have been considered the mainstay in controlling the B. tabaci in agricultural production systems. In the late 1970s and 1980s, pyrethroids insecticides replaced the organophosphates (OPs) and organochlorine insecticides. But in the late 1990s these were also replaced by neonicotinoids and other compounds. Excessive use of the same active ingredient and increased use of insecticides within a given cropping system has led to the insecticides resistance development in B. tabaci against the OPs and pyrethroids18,19. For example, Naveen (2016) described that Asia 1 and Asia II 1 have evolved resistance against organophosphates (Chlorpyrifos, etc.) and pyrethroids (Deltamethrin, etc.) while Asia II 7 is still susceptible against these insecticides17. The mechanism underlying insecticides resistance has been reported in a recent study that described the whole genome sequence of Asia II 1 from Pakistan. They stated that Asia II 1 have 1294 genes with high impact variants including 14 genes have involved in insecticides resistance17. In other south Asian countries like Bangladesh and Nepal, they have a similar situation like India where Asia 1 and Asia II 5 acts as a dominant species followed by Asia II 1 respectively resulting in the dominance of Asia II 1 in other countries. This seems Asia II 1 is being dominant in other regions of the world.

In South East Asia, the largest number of sequences have been reported from Malaysia, where Asia 1 is dominant followed by MED and others. Interestingly, there is still no report of Asia II 1 from Malaysia whereas it has been found in some other countries in South East Asia like Cambodia, Vietnam and Thailand. In East Asia countries, the largest number of sequences have been reported from China where MED is dominant followed by MEAM1 and ~ 19 species have been found in China. Interestingly, Asia II 1 was recently reported from China where CLCuD is also recently introduced. This clearly shows the relationship of different species with specific begomoviruses diseases in a region. Japan 2 is dominant in other countries like Japan and South Korea whereas MED and MEAM1 are dominant in other countries of East Asia region. In the Middle East region MED and MEAM1 are found dominant in different countries where Asia II 1 is only reported from Syria in the region.

Why Asia II 1 became dominant in Pakistan especially in cotton regions?? There are few gestures and hypothesis by the previous reports from Pakistan. Previously, it has been reported that Asia II 1 is the vector of CLCuD causing begomoviruses/satellites in Punjab, Pakistan where its 1st and 2nd epidemics occurred and this disease has spread to Sindh and also reported from northwestern India. Recently, in a broad survey the 3rd epidemic of CLCuD has been reported from Pakistan and distinct disease complex is found associated with this disease20,21. The dominant strain was cotton leaf curl Multan virus (CLCuMuV-Raj) Rajasthan strain and same has been reported from India since 201522. Interestingly, during a nation-wide vector-based survey of begomoviruses in Pakistan it has been found that CLCuMuV-Raj strain is the dominant strain in whitefly found from cotton regions in the country and dominant species was Asia II 123 than shows the co-evolution of the tripartite (host-vector-virus) in the region.

Updated record of population surge and diversity of B. tabaci species in a region is critical for developing effective approaches for whitefly control and to prevent the spread of invasive species. This study reports the two species Asia II 1 and Asia II 7 with mainly predominance of the Asia II 1 on cotton crop in Punjab and Sindh province of Pakistan.

Asia II 1 has been remained dominant in the central region (Punjab where CLCuD is endemic) and MEAM1 have been predominantly found in the southern region (Sindh where TYLCD is endemic) for more than three decades. Asia II 1 and MEAM1 have been prevalent in the overlapping regions in Pakistan for a long time but even then, the MEAM1 could not succeed to displace indigenous species Asia II 1, as has been the global trend. There is persistence of Asia II 1 in the neighboring regions of Pakistan as well as in the northern and central regions of India as in the data shown in Fig. 6A. A recent report from India also reported the Asia II 1 abundance in the northern and central regions of the country7. These are basically the cotton growing areas of Pakistan and India. Ahmed et al.24 directly compare the host suitability between the Asia II 1 and MEAM1 performed similarly across all hosts but its longevity and fecundity is high on tomato plants while Asia II 1 survived best on the cotton plants. Ahmed et al.25 reported first time the association of CLCuD incidence with the identity and abundance of B. tabaci species and found out the high disease incidence with an abundance of Asia II 1. Then Pan et al.26 directly compared the transmission efficiency of CLCuMuV in four cryptic species, two native species (Asia 1 and Asia II 1) and two invasive species (MEAM1 and MED) and reported that CLCuMuV is the most efficiently transmitted by the Asia II 1. So, might be agroecological niches which is the result of specific tripartite interaction (host, virus, and vector) is more suitable for the persistence abundance of Asia II 1 in this region.

In this data, Asia 1 is not found while it has been previously reported from both Punjab and Sindh13,25. In 2017, updated data was only found in the Sindh region by Masood et al.12. But in few latest reports of the genetic diversity in Pakistan, Asia 1 is not found15,23. These reports align with the result of this study.

Because of the advancement of the high throughput a cost-effective technologies, instead of relying on a single mitochondrial gene, scientists used whole genome wide and integrated approach to accurately species identification of the B. tabaci27. Whole genome data of MEAM1, MED, and Asia II 1 have been available for comparative and evolutionary genomic studies11,28,29. These studies lay the foundation for the pan genomics studies which have the potential to explain the difference between invasive and native dominance of B. tabaci.

Materials and methods

Scenario of cotton production and sap-sucking insect infestation

The cotton production data was collected from the major cotton growing areas of Pakistan. The information was extracted from Pakistan Economic Survey, 2020–2021 (https://www.finance.gov.pk/survey/chapters_21/02-Agriculture). Similarly, all the sap sucking insect infestation data was collected from the surveys available on the website of Pest Warning and Quality Control of Pesticides (PWQC), Government of Punjab, Pakistan (http://pestwarning.agripunjab.gov.pk/sucking-insect-pests). This data in PWQC is made available after pest scouting where pest scouting teams survey the cotton growing areas of Punjab on regular basis (40–50 random fields/week). The areas with 100 percent pest infestation were termed as hotspots.

Collection of whitefly samples

Adult whiteflies (B. tabaci) were collected from major cotton growing areas from 17 different geographical locations of Punjab, and Sindh province of Pakistan during the year 2017–2020. During the survey, the insect samples were collected randomly (in a zig-zag pattern) from the underside of the leaves using a handheld aspirator. About 20 adult whiteflies were collected from each locality and were kept in 95% ethanol and stored at – 20 °C for further experiments. The survey covered 14 districts of Punjab and 2 districts of Sindh province of Pakistan.

DNA extraction

Genomic DNA was extracted from 82 individual adult whiteflies. The extraction of DNA was performed using the method described by Zhang (1998) with the following manipulations30. Adult whitefly was blotted on filter paper to absorb water and grinded in 300 µL CTAB buffer (100 mM Tris–HCl, 20 mM EDTA, and 1.4 M NaCl consisting of 0.2% β-mercaptoethanol). This mixture after grinding was taken in a microfuge tube and incubated for 15 min at 65 °C, and then one volume of chloroform was added and mixed it manually. The mixture placed in a centrifuge and spun at 13,000 rpm for 4 min and supernatant was collected. One volume of isopropanol was added and content was incubated for 30 min. The mixture was centrifuged at 12,000 rpm for 10 min and remove the supernatant. The remained pellet was washed with 70% ethanol twice. The pellet was dried at room temperature and dissolved in nuclease-free water (Thermo Fisher Scientific, Wilmington, USA). The quality and concentration of DNA was checked by using Nanodrop 2000/2000c spectrophotometer (Thermo Fisher Scientific, Wilmington, USA) and then was stored at − 20 °C for downstream processing.

Molecular analyses of B. tabaci by mtCO1

The whitefly 3′-mtCO1 gene fragment (approximately 850 bases) can be amplified by polymerase chain reaction (PCR) by universal primers31. PCR was carried out in a total volume of 20 µL reaction tube containing 10 µL DreamTaq Green PCR Master Mix (Thermo Fischer Scientific), 0.5 pmol µL−1 of each primer (forward/reverse), 2 µL DNA (20 ng µL−1 whitefly DNA), and double-distilled water. This reaction was set up in the PCR machine (Bio-Rad, USA). The PCR conditions comprised of initial denaturation for 5 min at 94 °C, followed by 35 cycles of 94 °C for 30 s, 52 °C annealing for 1 min, 72 °C for 1 min, with a final extension of 10 min at 72 °C. The DNA was analyzed by using gel documentation system (Bio-Rad, USA). Successfully amplified products were excised and purified using Thermo GeneJET gel extraction kit (Thermo Fisher Scientific).

Cloning, sequencing, and data analyses

The purified products were directly ligated in PTZ57R/T plasmid vector (Thermo Fischer Scientific) and transformed in competent cells of Escherichia coli (TOP10 strain). Confirmed clones were selected and the sequence was determined by automated bi-directional, Sanger sequencing (Genomics and Bioinformatics Research Unit, USDA-ARS Stoneville, MS) using 3730XL ABI sequencer (Applied Biosystems, USA). The sequence reads of each clone were assembled by SeqMan in DNASTAR (Madison, WI) and a consensus sequence was saved and analyzed. First, each complete sequence was searched online by BLASTn (Basic Local Alignment Searching Tool (nucleotides) on NCBI database to identify similar sequences. For the identification of species of B. tabaci all the sequences identified in the current study were compared with the reference sequences of the known species of B. tabaci. For phylogenetic tree analysis, all these sequences were first aligned with the sequences of the reference isolates by MUSCLE in MEGA7 software32. A Neighbor-joining phylogenetic tree was reconstructed using all these sequences to infer the relationship of the current isolates with the previously known species.

The retrieving of mtCO1 sequences of B. tabaci

The available data of mtCO1 sequences of B. tabaci on GenBank was retrieved on 1st June 2021. A total 12,198 sequences are available under the organism’s name, Bemisia tabaci with mtCO1 gene. A major list was prepared in excel and filtered for the desired information. There were some isolates in which country name was not mentioned by the sequence submitter, so for these putative sequences, submitter’s country name was considered. Similarly, for many sequences sample collection date was missing so for that used the submission date and differentiated these dates (by bold for submission date used instead of actual collection date). For each country, sequences were retrieved based on the accession number against the name of the country in the list. The total final number of sequences from Asia used in the current study were 5142 isolates. For Pakistan, the reporting province name of each sequence was retrieved whereas, for India, zone names were also retrieved for 698 sequences.

Sequence analysis from the countries of Asia

We first filtered the data based on the country names for example for Pakistan, isolated all the sequences reported from Pakistan. Then we did their phylogenetic tree analysis to identify their species. Similarly, for other countries, their isolates were separated and analyses for the identification of their species were done. In the current study, Asian countries from three regions; South Asia, East Asia and Southeast Asia were checked for the B. tabaci presence and its species were determined for each isolate from these countries. Moreover, the countries of Middle East were also checked, as previously Asia II 1 was also reported from Syria (a country from Middle East) because south Asian countries have been good trading partner with the countries of the Middle East.

Supplementary Information

Supplementary Information 1. (14.3KB, docx)
Supplementary Information 2. (197.9KB, xlsx)

Acknowledgements

This material is based upon work supported by the "Pak-US cotton productivity enhancement program" of the International Center for Agricultural Research in the Dry Areas (ICARDA) funded by the United States Department of Agriculture (USDA), Agricultural Research Service (ARS), under agreement No. 58-6402-0-178F. Any opinions, findings, conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the USDA or ICARDA. The research work was also funded by Punjab Agricultural Research Board. NA and SH are funded by Higher Education Commission, Pakistan.

Author contributions

MAM, SH and STM did the experiments. NA and IA performed sequencing and phylogenetic analyses. MAM wrote the manuscript. SM and IA edited the manuscript. SM conceived the idea and supervised whole study.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-022-05612-1.

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